Network of devices forming a diagnostic system

ABSTRACT

The present invention relates to the field of systems and methods of diagnosis of apparatuses constituting a vast machine-to-machine communication network. The system proposed is based on a virtual network linking the various apparatuses so as to form a hierarchical tree. This virtual network is reliant on the network for real communication between the apparatuses. However, the topology of the virtual network is independent of that of the real network. Each apparatus includes a diagnostic agent offering local self-diagnostic capabilities. Each apparatus enables offering a state of its operation and of the operation of the entire sub-network of which it is the father. The self-diagnostic capabilities of an apparatus are implemented either locally by the apparatus, or within apparatuses of its close network environment as a function of the capabilities of the various items of equipment.

The present invention relates to the field of systems and methods fordiagnosing apparatuses that constitute a vast machine-to-machinecommunication network. More particularly, the invention will relate tothe hierarchical architecture of a diagnostic network.

The invention concerns a large number of apparatuses operating in anetwork. These apparatuses may for example be in the form of sensors ina town or in a building. The apparatuses are characterised by lowresources. They are typically designed to be battery-operated. It istherefore advantageous for them to use as few resources as possible, andmore particularly energy.

When administering a network of apparatuses of this type, it isnecessary to be able to monitor the network and diagnose its operatingstatus. For this purpose, various diagnostic systems are known. Thesesystems are generally based on a central diagnostic server thatcentralises the alerts from the apparatuses of the network. Referencecan be made to SNMP systems (Simple Network Management Protocol), and tothe system known by the name of “Automatic Computing” by IBM, whichcomprises a self-repair mechanism for on-board systems. Reference canalso be made to the OMA-DM system (Open Mobile Alliance—DeviceManagement).

This server sends requests to each apparatus forming the network ofapparatuses to be diagnosed. For this purpose, the diagnostic serverestablishes point-to-point communications destined for each apparatus.The diagnostic operations are controlled by the central server. Thisrequires each diagnostic phase to implement a set of communicationsbetween the central server and the various monitored apparatuses.

When the size of the network administered increases, the communicationneeds involved in this diagnosis increase exponentially. It alsorequires the use of a large number of communication resources within theadministered apparatuses.

The invention proposes a system and methods for hierarchical diagnosisthat enable limiting the resources necessary for its operation withineach involved apparatus. A further objective is to be able to takecharge of a very large-scale network. The proposed system is based on avirtual network that links the various apparatuses in order to form ahierarchical tree. This virtual network is based on the network of realcommunication between the apparatuses. However, the topology of thevirtual network is independent from that of the real network. Eachapparatus comprises a diagnostic agent that provides localself-diagnostic capacities. Each apparatus enables providing a state ofits own operation and of the operation of the entire sub-network ofwhich it is the father. The self-diagnostic capacities of an apparatusare implemented either locally on the apparatus, or within apparatusesof its close network environment, depending on the capacities of thevarious devices.

The hierarchical communication between the server and the apparatusesallows reducing the communications necessary for administration of thesystem. The local diagnostic and local self-repair capacities allowreducing the number of necessary communications.

The invention relates to a device comprising communication means forcommunicating within a physical communication network having a set ofapparatuses which comprises local self-diagnostic means; means forcontrolling a virtual hierarchical communication network with the set ofapparatuses within the physical communication network, and means fordetermining a diagnostic status relating to the result of the localself-diagnostic means and of the self-diagnostic means of theapparatuses that are dependent on said device in said hierarchicalcommunication network.

According to a particular embodiment of the invention, theself-diagnostic means comprise a set of diagnostic agents relating tolocal functionalities of the apparatus.

According to a particular embodiment of the invention, theself-diagnostic means further comprise diagnostic agents relating toexternal functionalities belonging to other apparatuses of thecommunication network.

According to a particular embodiment of the invention, operation of theself-diagnostic means is governed by a set of dynamic rules.

According to a particular embodiment of the invention, theself-diagnostic means further comprise self-repair means.

According to a particular embodiment of the invention, theself-diagnostic means further comprise means for responding to a requestdemanding the status of the entire sub-network of which the device isthe root within the virtual communication network.

According to a particular embodiment of the invention, theself-diagnostic means further comprise means for uplinking a locallydetected malfunction according to the type of malfunction.

According to a particular embodiment of the invention, theself-diagnostic means further comprise means for producing a diagnosisin an autonomous self-diagnostic mode, by using diagnostic agents thatrepresent only local functionalities.

According to a particular embodiment of the invention, theself-diagnostic means further comprise means for producing a diagnosisaccording to a recursive self-diagnostic mode, by using diagnosticagents that represent local functionalities and one external object.

According to a particular embodiment of the invention, theself-diagnostic means further comprise means for producing a diagnosisaccording to a collaborative self-diagnostic mode, by using diagnosticagents that represent local functionalities and multiple externalobjects.

The invention also relates to a network of apparatuses as just describedbriefly above, which together form a system for diagnosing said network.

The aforementioned features of the invention, as well as others, willbecome more apparent from reading the following description of anembodiment, said description being provided in relation to theaccompanying drawings, in which:

FIG. 1 illustrates the concept of a virtual network of real networksused in an embodiment of the invention.

FIG. 2 shows the architecture of a device of the network, comprising aself-diagnostic module.

FIG. 3 shows the autonomous self-diagnostic mode.

FIG. 4 shows the recursive self-diagnostic mode.

FIG. 5 shows the collaborative self-diagnostic mode.

FIG. 6 is a flow chart showing a self-diagnostic operation.

The invention falls within the context of large-scale networks ofdevices communicating in a machine-to-machine mode. The devices may beapparatuses with very low resources, such as simple sensors that will bereplaced when they run out of energy. These devices have communicationcapacities typically involving wireless communication. This can be anytechnology of the Bluetooth or Wi-Fi type, or wireless telephonycommunication of the GSM type. Typically, the networks concerned will beheterogeneous. The physical network can therefore be based on a set ofwired or wireless technologies for connecting the various devices.

FIG. 1 shows a network of nine devices. These devices are interconnectedby a physical communication network. These physical communication linksare shown in the drawing by a set of double arrows. It can be seen that,according to the physical network, the node 1 for example cancommunicate with the node 2 and the node 7. The node 2, for its part,can communicate with the nodes 4, 1 and 6, and so on. This physicalnetwork can have any type of topology.

A virtual communication network is constructed on top of this physicalnetwork. This virtual communication network has a typically hierarchicaltopology. This topology is implemented in the form of a tree. Thevirtual network therefore typically has a root. This root constitutesthe master diagnostic server of the system. A hierarchical path thenconnects this root to the set of nodes of the network. In the example inFIG. 1, the node 1 is the root node. The root node 1 has a single son,which is the node 2. Although physically connected to the node 7, thenode 1 is not the father of the node 7 in the virtual network. In saidvirtual network, the path between the node 1 and the node 7 passes viathe nodes 2 and 6. It is also found that the node 2 is connected to thenode 3 in the virtual network, whereas these two nodes are notphysically connected.

The self-diagnostic approach designed for large-scale machine-to-machinenetworks is based on a collection of local diagnostic agents that carryout the diagnostic operations in the apparatuses. These agents operatein an ecosystem known as the self-diagnostic module. They form a virtualcollaboration network according to a basic configuration that isself-configurable according to defined and modifiable rules. The agentsmonitor the state of their devices and, if applicable, carry out thediagnostics and corrections autonomously, and notify the hierarchicallevel above them of the changes in operating states.

This system enables, at the top of each hierarchical level of thisnetwork, including at the top of the system, having an overview of theoperating state of the underlying devices, taking into account the factthat each operating state at a higher level incorporates a summarisedstate of devices at lower levels.

Each device in the network comprises its own self-diagnostic module 2.6that executes its own set of diagnostic agents.

The self-diagnostic modules implement all the usual functions whichpermit execution of the diagnostic agents, and ensure conformity withthe specific diagnostic strategies relating to the concerned devices.

The purpose of the self-diagnostic modules is to implement the followingfunctions: self-diagnostics with warning notifications, diagnostics ofremote and/or autonomous apparatuses, and proactive detection and repairof malfunctions as soon as possible.

The self-diagnostic approach is suitable for very large-scale networkswhere administration of the devices affects costs. The flexibility isthe result of an approach based on the use of a set of rules that allowthe diagnostic rules to be updated or deactivated independently, with astrategy based on network administration feedback. The logic of therules that produce the diagnostics is separate from the processingcomponents that execute these rules, in the same way that an engine forexecution of a script language is separate from the executed scripts.The aforementioned diagnostic agents are instances of sequences ofdiagnostic rules.

The diagnostic rules describe how the diagnostic-oriented logic and,therefore, the diagnostic agent are applied to the components thatrepresent an atomic part of the status of the apparatuses. These atomicparts are known as monitored objects. The rules anticipate diagnosticresults and further describe what actions must be taken. Differentreactions to the diagnosis are possible from amongst the following:taking no action, generating a notification or initiating a self-repairprocedure.

The concept of monitored objects can be extended. Instead of simplyrepresenting local functionalities of the apparatus, the monitoredobjects may also represent external functionalities. For example, alocal monitored object can represent the status of a neighbouringapparatus in the network. In this case, the application of the localrules results in the diagnosis of two apparatuses by addressing a singleapparatus. It is possible to multiply this arrangement and have, withina single apparatus, a set of monitored objects representing one or moreexternal apparatuses. This therefore provides a diagnosis at the levelof the node which produces a diagnosis in the group of apparatuses.

The strategy of triggering a self-diagnosis must be established for eachapparatus. The diagnosis can be initiated periodically by a permanentmonitoring strategy, or triggered by random events that are dependent onthe type of service set up.

FIG. 2 shows the architecture of a device of the network 2.1 comprisinga self-diagnostic module 2.6. This module comprises a database 2.2 thatenables storing different objects stored in this diagnostic module. Thisdatabase further stores the structure of the virtual network, forexample references on the sons of the current apparatus, as well as onthe father. In particular, the module comprises a status 2.3 thatrepresents the operating state of the device. Operation of this moduleis governed by a set of rules 2.4. These rules are dynamic, and allowsetting the status 2.3 out, as well as, if applicable, the actions aimedat repairing a malfunction. The module comprises a set 2.5 of monitoredobjects. These objects are elementary software objects that representatomic parts of the apparatus, and/or external functionalities withinremote apparatuses.

The diagnostic agents that produce the diagnostics can operate in 3different modes. The first mode is known as the autonomousself-diagnostic mode. In this mode, the apparatus performs a localdiagnosis using the diagnostic agents representing only localfunctionalities. This mode is shown in FIG. 3, which shows an apparatus3.3 that produces its self-diagnostic status. This status is thentransferred via the virtual network 3.2 to a diagnostic server 3.1.

A second mode is known as the recursive self-diagnostic mode. In thismode, the apparatus performs a diagnosis using the local diagnosticagents representing local functionalities and an external object. Thismode is shown in FIG. 4, which shows the object 4.5 performing itsself-diagnosis. Its status is transmitted to the object 4.4. This object4.4 also performs its self-diagnosis, the result of which it aggregateswith the result received from the object 4.5. The resulting status issent to the object 4.3, which does the same thing. The status of theobject 4.3 therefore represents the operating state of the chain ofobjects 4.3, 4.4 and 4.5.

A third mode is known as the collaborative mode. In this mode, theapparatus performs a diagnosis of nodes on a set of monitored objectsrepresenting its local functionalities and multiple external objects.This mode is particularly suitable for networks of apparatuses with astar topology. This mode is shown in FIG. 5, which shows the object 5.3performing the diagnosis of the entire cluster of objects 5.3, 5.4, 5.5and 5.6.

These three types of architecture can be combined and coexist in asingle network. The self-diagnostic module of a root can be configuredto apply the diagnostic function recursively to a set of apparatuses, soas to define the operational status of a cluster of apparatuses. Thecombination of the recursive and collaborative modes enables setting thediagnostic of a cluster of apparatuses out, by addressing only the rootnode of this cluster. It is not necessary to separately address thedifferent nodes in order to obtain a diagnosis of the network as awhole. A request sent to a root node is sufficient.

It can thus be appreciated that, according to its location in thenetwork, a node contains a set of monitored objects corresponding to itsown Internet functionalities, and optionally a set of monitored objectscorresponding to external apparatuses of its network environment.Typically this involves its sons in the topology of the built virtualnetwork.

When a malfunction is detected on an apparatus of the network, actionsof several types can be undertaken according to the category of themalfunction. The malfunctions will be classified for example in at leasttwo categories, i.e. a first category of critical malfunctions, and asecond category of slight malfunctions. Other categories can be definedif needed. If the malfunction is critical, it will imply an uplinktransfert of this status to the father of the apparatus associated withthe identifier of the faulty apparatus. If the malfunction is simplyslight, the apparatus identifier will not be transferred uplink. In anynode of the tree, it is possible to determine in the sub-tree-son that amalfunction has occurred. An aggregation of all of the nodes undergoinga critical malfunction is performed. The identifier of all of thesenodes is thus obtained. If the malfunction is critical, it is possibleto enter into direct communication with the faulty apparatus. If themalfunction is slight, a discovery request will be sent, which willbrowse the sub-tree in order to uplink the identifier of the faultynode. This discovery step will be performed only if needed.

The allocation of a category to a given malfunction is performed by theself-diagnostic rules, and can therefore be dynamically modified. It isthus possible to configure finely and dynamically the malfunctions thatwill be uplink to the root of the network, and those that remain local.

As far as possible, it is attempted to repair the malfunctions at thelocal level. The rules define a set of repair actions that can beundertaken in order to attempt to correct the problem when it isdetected. These actions may comprise for example restarting theapparatus, or restoring a set of default parameters stored by theapparatus or by a neighbouring apparatus in the network. Applying localrepair rules during the detection of a malfunction limits the need forcommunication between the root and the malfunctioning nodes.

Advantageously, a node has rules that allow it to reconfigure thevirtual network in order to face up to malfunctions that affect itsoperation. For example, the loss of a physical communication link can becorrected by modification of the topology of the virtual network. Thesame can apply if a node is overloaded whilst it is acting as father fora large number of nodes of the virtual network, and reconfiguration canalleviate its load.

By default, the diagnostic intelligence associated with localfunctionalities of an apparatus is located in this apparatus. However,it is possible for the capacities of the apparatus to be limited to theextent where this is not possible. Delocalisation of this intelligenceis then allowed within another apparatus in the close networkenvironment of this apparatus. Typically, this will be the father of theapparatus in the topology of the virtual network. However, this is notcompulsory. Nevertheless, it is advantageous for the apparatus to beclose in the virtual network, so as to limit the communications betweenthe diagnostic intelligence host apparatus and the apparatus that is thetarget of this diagnosis.

FIG. 6 is a flowchart showing a self-diagnostic operation. During afirst step 6.1, a malfunction is detected by one of the diagnosticagents. Since a malfunction has been detected, it is important todetermine its primary cause. In fact, it is common for a firstmalfunction to imply a series of secondary malfunctions derived fromthis first malfunction. It is therefore important to trace the firstmalfunction and its primary cause, which is performed in the step 6.2.Application of the rules then leads to a step 6.3 of self repair, whenthis is possible, depending on the identified cause. Once this selfrepair step has been attempted, it is important to verify the correctionof the malfunction during a step 6.4. The result is then reported to thefather in the virtual network, which is the step 6.5.

The invention claimed is:
 1. A device for communicating within aphysical communication network with a set of apparatuses, comprising: atleast one local diagnostic agent relating to local functionalities ofthe device for local self-diagnostics in the device; a database allowingmanaging a virtual hierarchical communication network with the set ofapparatuses within the physical communication network; and aself-diagnostic module, executed by a processor, for determining adiagnostic status relating to a result of each local diagnostic agent ofthe device and of local diagnostic agents of the apparatuses that aredependent on said device in said virtual hierarchical communicationnetwork relating to external functionalities belonging to theseapparatuses, wherein the self-diagnostic module is further configuredfor uplinking a locally detected malfunction according to a type ofmalfunction.
 2. The device according to claim 1, wherein operation ofthe self-diagnostic module is governed by a set of dynamic rules.
 3. Thedevice according to claim 1, wherein the self-diagnostic module isadapted to perform self-repair operations.
 4. The device according toclaim 1, wherein the self-diagnostic module is further configured forresponding to a request demanding the status of an entire sub-network ofwhich the device is a root within the virtual communication network. 5.The device according to claim 1, wherein the self-diagnostic module isfurther adapted for producing a diagnosis in an autonomousself-diagnostic mode, by using diagnostic agents that represent onlylocal functionalities.
 6. The device according to claim 1, wherein theself-diagnostic module is further configured for producing a diagnosisin a recursive self-diagnostic mode, by using diagnostic agents thatrepresent local functionalities and one external object.
 7. The deviceaccording to claim 1, wherein the self-diagnostic module is furtherconfigured for producing a diagnosis in a collaborative self-diagnosticmode, by using diagnostic agents that represent local functionalitiesand multiple external objects.
 8. A network of apparatuses according toclaim 1, which form a system for diagnosing said network.